use crate::errors::AppError;
use serde::Deserialize;
use std::process::Stdio;
use std::sync::Arc;
use tokio::io::AsyncWriteExt;
use tokio::process::Command;
const DEFAULT_EMBED_TIMEOUT_SECS: u64 = 300;
fn embed_timeout() -> std::time::Duration {
let secs = std::env::var("SQLITE_GRAPHRAG_EMBED_TIMEOUT_SECS")
.ok()
.and_then(|v| v.parse::<u64>().ok())
.filter(|&n| (10..=3_600).contains(&n))
.unwrap_or(DEFAULT_EMBED_TIMEOUT_SECS);
std::time::Duration::from_secs(secs)
}
fn build_single_schema(dim: usize) -> String {
format!(
r#"{{"type":"object","properties":{{"embedding":{{"type":"array","items":{{"type":"number"}},"minItems":{dim},"maxItems":{dim}}}}},"required":["embedding"],"additionalProperties":false}}"#
)
}
fn build_batch_schema(dim: usize) -> String {
format!(
r#"{{"type":"object","properties":{{"items":{{"type":"array","items":{{"type":"object","properties":{{"i":{{"type":"integer"}},"v":{{"type":"array","items":{{"type":"number"}},"minItems":{dim},"maxItems":{dim}}}}},"required":["i","v"],"additionalProperties":false}}}}}},"required":["items"],"additionalProperties":false}}"#
)
}
#[derive(Clone, Debug)]
pub struct LlmEmbedding {
flavour: EmbeddingFlavour,
binary: std::path::PathBuf,
model: String,
codex_schemas: Arc<parking_lot::Mutex<CodexSchemaFiles>>,
}
#[derive(Debug, Default)]
struct CodexSchemaFiles {
single: Option<(usize, Arc<tempfile::NamedTempFile>)>,
batch: Option<(usize, Arc<tempfile::NamedTempFile>)>,
}
#[derive(Clone, Copy, Debug, PartialEq, Eq, Deserialize)]
pub enum EmbeddingFlavour {
Claude,
Codex,
}
impl EmbeddingFlavour {
pub fn as_str(self) -> &'static str {
match self {
Self::Claude => "claude",
Self::Codex => "codex",
}
}
}
#[derive(Debug, Deserialize)]
struct EmbeddingResponse {
embedding: Vec<f32>,
}
#[derive(Debug, Deserialize)]
struct BatchEmbeddingResponse {
items: Vec<BatchEmbeddingItem>,
}
#[derive(Debug, Deserialize)]
struct BatchEmbeddingItem {
i: usize,
v: Vec<f32>,
}
pub fn resolve_real_binary(path: &std::path::Path) -> std::path::PathBuf {
if let Ok(canonical) = std::fs::canonicalize(path) {
if is_elf_binary(&canonical) {
return canonical;
}
if let Some(exec_target) = extract_exec_target_from_shim(&canonical) {
if exec_target.exists() && is_elf_binary(&exec_target) {
return exec_target;
}
}
return canonical;
}
path.to_path_buf()
}
fn is_elf_binary(path: &std::path::Path) -> bool {
std::fs::read(path)
.map(|bytes| bytes.len() >= 4 && bytes[..4] == [0x7f, b'E', b'L', b'F'])
.unwrap_or(false)
}
fn extract_exec_target_from_shim(path: &std::path::Path) -> Option<std::path::PathBuf> {
let content = std::fs::read_to_string(path).ok()?;
if !content.starts_with("#!") {
return None;
}
for line in content.lines().rev() {
let trimmed = line.trim();
if trimmed.starts_with("exec ") {
let after_exec = trimmed.strip_prefix("exec ")?;
let binary = after_exec.split_whitespace().next()?;
return Some(std::path::PathBuf::from(binary));
}
}
None
}
fn claude_embed_model() -> String {
std::env::var("SQLITE_GRAPHRAG_CLAUDE_EMBED_MODEL")
.unwrap_or_else(|_| "claude-sonnet-4-6".to_string())
}
fn codex_embed_model() -> String {
std::env::var("SQLITE_GRAPHRAG_CODEX_EMBED_MODEL").unwrap_or_else(|_| "gpt-5.5".to_string())
}
impl LlmEmbedding {
pub fn detect_available() -> Result<Self, AppError> {
Self::oauth_only_enforce()?;
if let Ok(path) = which::which("codex") {
return Ok(Self {
flavour: EmbeddingFlavour::Codex,
binary: resolve_real_binary(&path),
model: codex_embed_model(),
codex_schemas: Arc::new(parking_lot::Mutex::new(CodexSchemaFiles::default())),
});
}
if let Ok(path) = which::which("claude") {
return Ok(Self {
flavour: EmbeddingFlavour::Claude,
binary: resolve_real_binary(&path),
model: claude_embed_model(),
codex_schemas: Arc::new(parking_lot::Mutex::new(CodexSchemaFiles::default())),
});
}
Err(AppError::Embedding(
"no LLM CLI found on PATH: install `codex` (0.130+) or `claude` (Claude Code 2.1+)"
.to_string(),
))
}
pub fn with_codex() -> Result<Self, AppError> {
Self::oauth_only_enforce()?;
let path = which::which("codex")
.map_err(|_| AppError::Embedding("`codex` not found on PATH".to_string()))?;
Ok(Self {
flavour: EmbeddingFlavour::Codex,
binary: resolve_real_binary(&path),
model: codex_embed_model(),
codex_schemas: Arc::new(parking_lot::Mutex::new(CodexSchemaFiles::default())),
})
}
pub fn with_claude() -> Result<Self, AppError> {
Self::oauth_only_enforce()?;
let path = which::which("claude")
.map_err(|_| AppError::Embedding("`claude` not found on PATH".to_string()))?;
Ok(Self {
flavour: EmbeddingFlavour::Claude,
binary: resolve_real_binary(&path),
model: claude_embed_model(),
codex_schemas: Arc::new(parking_lot::Mutex::new(CodexSchemaFiles::default())),
})
}
fn oauth_only_enforce() -> Result<(), AppError> {
if std::env::var("ANTHROPIC_API_KEY").is_ok() {
return Err(AppError::Validation(
"ANTHROPIC_API_KEY is set; v1.0.76 requires OAuth. \
unset it and use `claude login` instead."
.into(),
));
}
if std::env::var("OPENAI_API_KEY").is_ok() {
return Err(AppError::Validation(
"OPENAI_API_KEY is set; v1.0.76 requires OAuth. \
unset it and use `codex login` instead."
.into(),
));
}
Ok(())
}
pub fn embed_passage(&self, text: &str) -> Result<Vec<f32>, AppError> {
self.invoke_with_prefix(crate::constants::PASSAGE_PREFIX, text)
}
pub fn embed_query(&self, text: &str) -> Result<Vec<f32>, AppError> {
self.invoke_with_prefix(crate::constants::QUERY_PREFIX, text)
}
pub async fn embed_batch_async(
&self,
prefix: &str,
batch: &[(usize, String)],
) -> Result<Vec<(usize, Vec<f32>)>, AppError> {
let dim = crate::constants::embedding_dim();
if batch.is_empty() {
return Ok(Vec::new());
}
if batch.len() == 1 {
let (idx, text) = (&batch[0].0, &batch[0].1);
let v = self.invoke_single_async(prefix, text, dim).await?;
return Ok(vec![(*idx, v)]);
}
let mut prompt = format!(
"Generate {dim}-dimensional semantic embedding vectors for each numbered text below.\n\
Return a JSON object with an \"items\" array containing EXACTLY {n} items.\n\
Each item has \"i\" (the 1-based index) and \"v\" (the {dim}-float vector, values between -1 and 1).\n\n",
n = batch.len()
);
for (pos, (_, text)) in batch.iter().enumerate() {
prompt.push_str(&format!("{}: {prefix}{text}\n", pos + 1));
}
let stdout = match self.flavour {
EmbeddingFlavour::Claude => {
self.invoke_claude(&prompt, &build_batch_schema(dim))
.await?
}
EmbeddingFlavour::Codex => {
let schema = self.codex_schema_file(dim, true)?;
self.invoke_codex(&prompt, schema.path()).await?
}
};
let parsed: BatchEmbeddingResponse = parse_llm_json(&stdout).map_err(|e| {
AppError::Embedding(format!(
"LLM batch embedding response parse failed: {e}; raw={stdout}"
))
})?;
if parsed.items.len() != batch.len() {
return Err(AppError::Embedding(format!(
"LLM batch returned {} items, expected {} (G42/S2 coverage check)",
parsed.items.len(),
batch.len()
)));
}
let mut out: Vec<Option<Vec<f32>>> = vec![None; batch.len()];
for item in parsed.items {
if item.i == 0 || item.i > batch.len() {
return Err(AppError::Embedding(format!(
"LLM batch item index {} out of range 1..={}",
item.i,
batch.len()
)));
}
if item.v.len() != dim {
return Err(AppError::Embedding(format!(
"LLM batch item {} returned {} dims, expected {dim}; \
refusing to truncate or pad silently (G42/C5)",
item.i,
item.v.len()
)));
}
out[item.i - 1] = Some(item.v);
}
let mut result = Vec::with_capacity(batch.len());
for (pos, slot) in out.into_iter().enumerate() {
let v = slot.ok_or_else(|| {
AppError::Embedding(format!(
"LLM batch response is missing item index {} (G42/S2 coverage check)",
pos + 1
))
})?;
result.push((batch[pos].0, v));
}
Ok(result)
}
fn invoke_with_prefix(&self, prefix: &str, text: &str) -> Result<Vec<f32>, AppError> {
let dim = crate::constants::embedding_dim();
let inner = self.invoke_single_async(prefix, text, dim);
match tokio::runtime::Handle::try_current() {
Ok(handle) => tokio::task::block_in_place(|| handle.block_on(inner)),
Err(_) => crate::embedder::shared_runtime()?.block_on(inner),
}
}
async fn invoke_single_async(
&self,
prefix: &str,
text: &str,
dim: usize,
) -> Result<Vec<f32>, AppError> {
let prompt = format!("{prefix}{text}");
let stdout = match self.flavour {
EmbeddingFlavour::Claude => {
self.invoke_claude(&prompt, &build_single_schema(dim))
.await?
}
EmbeddingFlavour::Codex => {
let schema = self.codex_schema_file(dim, false)?;
self.invoke_codex(&prompt, schema.path()).await?
}
};
let parsed: EmbeddingResponse = parse_llm_json(&stdout).map_err(|e| {
AppError::Embedding(format!(
"LLM embedding response parse failed: {e}; raw={stdout}"
))
})?;
if parsed.embedding.len() != dim {
return Err(AppError::Embedding(format!(
"LLM returned {} dims, expected {dim}; \
refusing to truncate or pad silently (G42/C5)",
parsed.embedding.len()
)));
}
Ok(parsed.embedding)
}
fn codex_schema_file(
&self,
dim: usize,
batch: bool,
) -> Result<Arc<tempfile::NamedTempFile>, AppError> {
let mut guard = self.codex_schemas.lock();
let slot = if batch {
&mut guard.batch
} else {
&mut guard.single
};
if let Some((cached_dim, file)) = slot {
if *cached_dim == dim {
return Ok(Arc::clone(file));
}
}
let content = if batch {
build_batch_schema(dim)
} else {
build_single_schema(dim)
};
let file = tempfile::Builder::new()
.prefix("sqlite-graphrag-embed-schema-")
.suffix(".json")
.tempfile()
.map_err(|e| AppError::Embedding(format!("schema tempfile create failed: {e}")))?;
std::fs::write(file.path(), content)
.map_err(|e| AppError::Embedding(format!("schema tempfile write failed: {e}")))?;
let file = Arc::new(file);
*slot = Some((dim, Arc::clone(&file)));
Ok(file)
}
async fn invoke_claude(&self, prompt: &str, schema: &str) -> Result<String, AppError> {
let mut cmd = Command::new(&self.binary);
cmd.arg("-p")
.arg(prompt)
.arg("--model")
.arg(&self.model)
.arg("--json-schema")
.arg(schema)
.arg("--output-format")
.arg("json")
.arg("--strict-mcp-config")
.arg("--mcp-config")
.arg(r#"{"mcpServers":{}}"#)
.arg("--settings")
.arg(r#"{"hooks":{}}"#)
.arg("--dangerously-skip-permissions")
.env_clear()
.env("PATH", std::env::var("PATH").unwrap_or_default())
.env("HOME", std::env::var("HOME").unwrap_or_default())
.stdin(Stdio::null())
.stdout(Stdio::piped())
.stderr(Stdio::piped())
.kill_on_drop(true);
if let Some(config_dir) = claude_embedding_config_dir() {
cmd.env("CLAUDE_CONFIG_DIR", &config_dir);
}
let output = tokio::time::timeout(embed_timeout(), cmd.output())
.await
.map_err(|_| {
AppError::Embedding(format!(
"claude embedding call timed out after {}s \
(override via SQLITE_GRAPHRAG_EMBED_TIMEOUT_SECS)",
embed_timeout().as_secs()
))
})?
.map_err(|e| AppError::Embedding(format!("claude spawn failed: {e}")))?;
if !output.status.success() {
return Err(AppError::Embedding(format!(
"claude exited with {}: stderr={}",
output.status,
String::from_utf8_lossy(&output.stderr)
)));
}
Ok(String::from_utf8_lossy(&output.stdout).into_owned())
}
async fn invoke_codex(
&self,
prompt: &str,
schema_path: &std::path::Path,
) -> Result<String, AppError> {
let mut child = build_codex_embedding_command(&self.binary, &self.model, schema_path)
.spawn()
.map_err(|e| AppError::Embedding(format!("codex spawn failed: {e}")))?;
if let Some(mut stdin) = child.stdin.take() {
stdin
.write_all(prompt.as_bytes())
.await
.map_err(|e| AppError::Embedding(format!("codex stdin write failed: {e}")))?;
}
let output = tokio::time::timeout(embed_timeout(), child.wait_with_output())
.await
.map_err(|_| {
AppError::Embedding(format!(
"codex embedding call timed out after {}s \
(override via SQLITE_GRAPHRAG_EMBED_TIMEOUT_SECS)",
embed_timeout().as_secs()
))
})?
.map_err(|e| AppError::Embedding(format!("codex wait failed: {e}")))?;
if !output.status.success() {
let stderr = String::from_utf8_lossy(&output.stderr);
if stderr.contains("request_user_input") {
return Err(AppError::Embedding(format!(
"codex requested interactive input in a headless embedding call \
(exit {}). This codex build ignores the non-interactive flags; \
upgrade codex (>= 0.134) or switch the embedding backend to \
claude by removing `codex` from PATH or installing `claude`. \
stderr={stderr}",
output.status
)));
}
return Err(AppError::Embedding(format!(
"codex exited with {}: stderr={stderr}",
output.status
)));
}
Ok(String::from_utf8_lossy(&output.stdout).into_owned())
}
}
fn claude_embedding_config_dir() -> Option<std::path::PathBuf> {
if let Ok(dir) = std::env::var("SQLITE_GRAPHRAG_CLAUDE_EMPTY_CONFIG_DIR") {
let path = std::path::PathBuf::from(dir);
if path.is_dir() {
return Some(path);
}
tracing::warn!(
target: "embedding",
path = %path.display(),
"SQLITE_GRAPHRAG_CLAUDE_EMPTY_CONFIG_DIR is set but not a directory; \
falling back to the managed empty config dir"
);
}
let home = std::env::var("HOME").ok()?;
let dir = std::path::Path::new(&home)
.join(".local/state/sqlite-graphrag")
.join("claude-empty-config");
if std::fs::create_dir_all(&dir).is_err() {
return None;
}
#[cfg(unix)]
{
use std::os::unix::fs::PermissionsExt;
let _ = std::fs::set_permissions(&dir, std::fs::Permissions::from_mode(0o700));
}
let creds = std::path::Path::new(&home).join(".claude/.credentials.json");
if creds.exists() {
let target = dir.join(".credentials.json");
if !target.exists() {
let _ = std::fs::copy(&creds, &target);
}
}
Some(dir)
}
fn build_codex_embedding_command(
binary: &std::path::Path,
model: &str,
schema_path: &std::path::Path,
) -> Command {
let mut cmd = Command::new(binary);
cmd.arg("exec")
.arg("-c")
.arg("sandbox_mode='read-only'")
.arg("-c")
.arg("approval_policy='never'")
.arg("--json")
.arg("--output-schema")
.arg(schema_path)
.arg("--ephemeral")
.arg("--skip-git-repo-check")
.arg("--sandbox")
.arg("read-only")
.arg("--ignore-user-config")
.arg("--ignore-rules");
if crate::extract::codex_compat::codex_supports_ask_for_approval() {
cmd.arg("--ask-for-approval").arg("never");
}
let codex_home = prepare_isolated_codex_home();
cmd.arg("--model")
.arg(model)
.arg("-")
.env_clear()
.env("PATH", std::env::var("PATH").unwrap_or_default())
.env("HOME", std::env::var("HOME").unwrap_or_default());
if let Some(ref ch) = codex_home {
cmd.env("CODEX_HOME", ch);
}
cmd.stdin(Stdio::piped())
.stdout(Stdio::piped())
.stderr(Stdio::piped())
.kill_on_drop(true);
cmd
}
fn prepare_isolated_codex_home() -> Option<std::path::PathBuf> {
let home = std::env::var("HOME").ok()?;
let real_auth = std::path::Path::new(&home).join(".codex/auth.json");
if !real_auth.exists() {
return None;
}
let base = std::path::Path::new(&home).join(".local/share/sqlite-graphrag");
let isolated = base.join(format!("codex-home-{}", std::process::id()));
let _ = std::fs::create_dir_all(&isolated);
let target = isolated.join("auth.json");
if !target.exists() {
let _ = std::fs::copy(&real_auth, &target);
}
Some(isolated)
}
fn parse_llm_json<T: serde::de::DeserializeOwned>(stdout: &str) -> Result<T, String> {
if let Ok(parsed) = serde_json::from_str::<T>(stdout) {
return Ok(parsed);
}
let mut last_agent_text: Option<String> = None;
for line in stdout.lines() {
let line = line.trim();
if line.is_empty() {
continue;
}
let Ok(event) = serde_json::from_str::<serde_json::Value>(line) else {
continue;
};
if event.get("type").and_then(|t| t.as_str()) != Some("item.completed") {
continue;
}
let item = match event.get("item") {
Some(i) => i,
None => continue,
};
if item.get("type").and_then(|t| t.as_str()) != Some("agent_message") {
continue;
}
if let Some(text) = item.get("text").and_then(|t| t.as_str()) {
last_agent_text = Some(text.to_string());
}
}
let text = last_agent_text
.ok_or_else(|| "no agent_message found in codex JSONL output".to_string())?;
serde_json::from_str::<T>(&text)
.map_err(|e| format!("codex agent_message text does not match schema: {e}; raw={text}"))
}
#[cfg(test)]
mod tests {
use super::*;
fn test_client(flavour: EmbeddingFlavour, binary: std::path::PathBuf) -> LlmEmbedding {
LlmEmbedding {
flavour,
binary,
model: "gpt-5.4".to_string(),
codex_schemas: Arc::new(parking_lot::Mutex::new(CodexSchemaFiles::default())),
}
}
#[test]
#[serial_test::serial(env)]
fn oauth_only_enforce_blocks_api_keys() {
unsafe {
std::env::set_var("ANTHROPIC_API_KEY", "test");
assert!(LlmEmbedding::oauth_only_enforce().is_err());
std::env::remove_var("ANTHROPIC_API_KEY");
std::env::set_var("OPENAI_API_KEY", "test");
assert!(LlmEmbedding::oauth_only_enforce().is_err());
std::env::remove_var("OPENAI_API_KEY");
}
assert!(LlmEmbedding::oauth_only_enforce().is_ok());
}
#[test]
fn flavour_as_str_is_stable() {
assert_eq!(EmbeddingFlavour::Claude.as_str(), "claude");
assert_eq!(EmbeddingFlavour::Codex.as_str(), "codex");
}
#[test]
fn single_schema_embeds_active_dim() {
let schema = build_single_schema(64);
assert!(schema.contains(r#""minItems":64"#));
assert!(schema.contains(r#""maxItems":64"#));
let parsed: serde_json::Value =
serde_json::from_str(&schema).expect("single schema must be valid JSON");
assert_eq!(parsed["properties"]["embedding"]["minItems"], 64);
}
#[test]
fn batch_schema_is_valid_json_and_unbounded_items() {
let schema = build_batch_schema(64);
let parsed: serde_json::Value =
serde_json::from_str(&schema).expect("batch schema must be valid JSON");
assert!(parsed["properties"]["items"].get("minItems").is_none());
assert_eq!(
parsed["properties"]["items"]["items"]["properties"]["v"]["minItems"],
64
);
}
#[test]
fn parse_llm_json_accepts_claude_json() {
let stdout = r#"{"embedding":[0.0,1.0,2.0]}"#;
let parsed: EmbeddingResponse = parse_llm_json(stdout).expect("claude JSON must parse");
assert_eq!(parsed.embedding, vec![0.0, 1.0, 2.0]);
}
#[test]
fn parse_llm_json_accepts_codex_jsonl() {
let stdout = r#"{"type":"thread.started","thread_id":"mock-thread-0"}
{"type":"item.completed","item":{"type":"agent_message","text":"{\"embedding\":[0.0,1.0,2.0]}"}}
{"type":"turn.completed","usage":{"input_tokens":1,"output_tokens":1}}"#;
let parsed: EmbeddingResponse = parse_llm_json(stdout).expect("codex JSONL must parse");
assert_eq!(parsed.embedding, vec![0.0, 1.0, 2.0]);
}
#[test]
fn parse_llm_json_rejects_jsonl_without_agent_message() {
let stdout = r#"{"type":"thread.started","thread_id":"mock-thread-0"}"#;
let err = parse_llm_json::<EmbeddingResponse>(stdout)
.expect_err("missing agent_message must fail");
assert!(err.contains("no agent_message"));
}
#[test]
fn parse_llm_json_accepts_batch_response() {
let stdout = r#"{"items":[{"i":1,"v":[0.0,1.0]},{"i":2,"v":[2.0,3.0]}]}"#;
let parsed: BatchEmbeddingResponse = parse_llm_json(stdout).expect("batch JSON must parse");
assert_eq!(parsed.items.len(), 2);
assert_eq!(parsed.items[0].i, 1);
assert_eq!(parsed.items[1].v, vec![2.0, 3.0]);
}
#[test]
fn codex_schema_file_is_created_once_and_reused() {
let client = test_client(
EmbeddingFlavour::Codex,
std::path::PathBuf::from("/bin/true"),
);
let first = client
.codex_schema_file(64, false)
.expect("schema file must be created");
let second = client
.codex_schema_file(64, false)
.expect("schema file must be reused");
assert_eq!(first.path(), second.path(), "same dim must reuse the file");
let batch = client
.codex_schema_file(64, true)
.expect("batch schema file must be created");
assert_ne!(
first.path(),
batch.path(),
"single and batch schemas are distinct files"
);
let content = std::fs::read_to_string(first.path()).expect("schema file must be readable");
assert!(content.contains(r#""minItems":64"#));
}
#[test]
fn codex_embedding_command_reads_prompt_from_stdin() {
let schema_path = std::env::temp_dir().join("sqlite-graphrag-embed-schema-test.json");
let cmd = build_codex_embedding_command(
std::path::Path::new("/bin/true"),
"gpt-5.4",
&schema_path,
);
let argv: Vec<String> = cmd
.as_std()
.get_args()
.filter_map(|arg| arg.to_str().map(|s| s.to_string()))
.collect();
assert!(
argv.iter().any(|arg| arg == "-"),
"codex embedding command must read prompt from stdin: {argv:?}"
);
assert!(
!argv.iter().any(|arg| arg.starts_with("passage: ")),
"prompt text must not be passed as argv: {argv:?}"
);
for required in &[
"exec",
"-c",
"sandbox_mode='read-only'",
"approval_policy='never'",
"--json",
"--output-schema",
"--ephemeral",
"--skip-git-repo-check",
"--sandbox",
"read-only",
"--ignore-user-config",
"--ignore-rules",
"--model",
"gpt-5.4",
] {
assert!(
argv.iter().any(|arg| arg == required),
"missing flag {required} in {argv:?}"
);
}
}
#[cfg(unix)]
#[test]
#[serial_test::serial(env)]
fn embed_passage_sends_prompt_to_codex_stdin() {
use std::os::unix::fs::PermissionsExt;
unsafe {
std::env::set_var("SQLITE_GRAPHRAG_EMBEDDING_DIM", "64");
}
let temp = tempfile::tempdir().expect("tempdir must exist");
let binary = temp.path().join("codex-stdin-check");
let script = r#"#!/usr/bin/env bash
set -euo pipefail
prompt="$(cat)"
if [[ "$prompt" != "passage: codex-cli" ]]; then
echo "unexpected stdin: $prompt" >&2
exit 41
fi
vals="0.0"
for _ in $(seq 2 64); do
vals="$vals,0.0"
done
payload="{\"embedding\":[$vals]}"
escaped="${payload//\"/\\\"}"
echo "{\"type\":\"item.completed\",\"item\":{\"type\":\"agent_message\",\"text\":\"$escaped\"}}"
"#;
std::fs::write(&binary, script).expect("mock codex script must be written");
let mut perms = std::fs::metadata(&binary)
.expect("mock codex metadata must exist")
.permissions();
perms.set_mode(0o755);
std::fs::set_permissions(&binary, perms).expect("mock codex must be executable");
let embedding = test_client(EmbeddingFlavour::Codex, binary);
let vector = embedding
.embed_passage("codex-cli")
.expect("stdin-backed codex embedding must succeed");
unsafe {
std::env::remove_var("SQLITE_GRAPHRAG_EMBEDDING_DIM");
}
assert_eq!(vector.len(), 64);
assert!(vector.iter().all(|value| *value == 0.0));
}
}